Scientific reports
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Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcomes compared with normotension, but it is difficult to predict because several factors have interactive and complex effects on the risk. The present study applied machine learning algorithms to develop models to predict hypotension after initiating CRRT. Among 2349 adult patients who started CRRT due to acute kidney injury, 70% and 30% were randomly assigned into the training and testing sets, respectively. ⋯ The XGB model showed the highest AUROC (0.828 [0.796-0.861]), and the DNN and LGBM models followed with AUROCs of 0.822 (0.789-0.856) and 0.813 (0.780-0.847), respectively; all machine learning AUROC values were higher than those obtained from disease-severity scores (AUROCs < 0.6). Although other definitions of hypotension were used such as a reduction of MAP ≥ 30 mmHg or a reduction occurring within 1 h, the AUROCs of machine learning models were higher than those of disease-severity scores. Machine learning models successfully predict hypotension after starting CRRT and can serve as the basis of systems to predict hypotension before starting CRRT.
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Oxylipins modulate the behavior of immune cells in inflammation. Soluble epoxide hydrolase (sEH) converts anti-inflammatory epoxyeicosatrienoic acid (EET) to dihydroxyeicosatrienoic acid (DHET). An sEH-inhibitor, TPPU, has been demonstrated to ameliorate lipopolysaccharide (LPS)- and sepsis-induced inflammation via EETs. ⋯ We conclude that TPPU administration decreases DHET post-burn. Furthermore, DHET downregulates key neutrophil immune functions and mRNA expression. Altogether, these data reveal that TPPU not only increases anti-inflammatory and inflammation resolving EET levels, but also prevents potential impairment of neutrophils by DHET in trauma.
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High-grade gliomas are notorious for a high recurrence rate even after curative resection surgery. Studies regarding the influence of scalp block on high-grade gliomas have been inconclusive, possibly because the condition's most important genetic mutation profile, namely the isocitrate dehydrogenase 1 (IDH1) mutation, had not been analyzed. ⋯ Multivariate Cox regression analysis revealed that scalp block (hazard ratio: 0.436, 95% confidence interval: 0.236-0.807, p = 0.0082), gross total resection (hazard ratio: 0.405, 95% confidence interval: 0.227-0.721, p = 0.0021), and IDH1 mutation (hazard ratio: 0.304, 95% confidence interval: 0.118-0.784, p = 0.0138) were associated with better PFS. Our results demonstrate that application of scalp block, regardless of IDH1 profile, is an independent factor associated with longer PFS for patients with high-grade glioma.